/* ----------------------------------------------------------------------
 * Project:      CMSIS DSP Library
 * Title:        arm_dot_prod_f32.c
 * Description:  Floating-point dot product
 *
 * $Date:        18. March 2019
 * $Revision:    V1.6.0
 *
 * Target Processor: Cortex-M cores
 * -------------------------------------------------------------------- */
/*
 * Copyright (C) 2010-2019 ARM Limited or its affiliates. All rights reserved.
 *
 * SPDX-License-Identifier: Apache-2.0
 *
 * Licensed under the Apache License, Version 2.0 (the License); you may
 * not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an AS IS BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "arm_math.h"

/**
  @ingroup groupMath
 */

/**
  @defgroup BasicDotProd Vector Dot Product

  Computes the dot product of two vectors.
  The vectors are multiplied element-by-element and then summed.

  <pre>
      sum = pSrcA[0]*pSrcB[0] + pSrcA[1]*pSrcB[1] + ... + pSrcA[blockSize-1]*pSrcB[blockSize-1]
  </pre>

  There are separate functions for floating-point, Q7, Q15, and Q31 data types.
 */

/**
  @addtogroup BasicDotProd
  @{
 */

/**
  @brief         Dot product of floating-point vectors.
  @param[in]     pSrcA      points to the first input vector.
  @param[in]     pSrcB      points to the second input vector.
  @param[in]     blockSize  number of samples in each vector.
  @param[out]    result     output result returned here.
  @return        none
 */

#if defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE)

#include "arm_helium_utils.h"


void arm_dot_prod_f32(
	const float32_t *pSrcA,
	const float32_t *pSrcB,
	uint32_t    blockSize,
	float32_t *result)
{
	f32x4_t vecA, vecB;
	f32x4_t vecSum;
	uint32_t blkCnt;
	float32_t sum = 0.0f;
	vecSum = vdupq_n_f32(0.0f);

	/* Compute 4 outputs at a time */
	blkCnt = blockSize >> 2U;
	while (blkCnt > 0U) {
		/*
		 * C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1]
		 * Calculate dot product and then store the result in a temporary buffer.
		 * and advance vector source and destination pointers
		 */
		vecA = vld1q(pSrcA);
		pSrcA += 4;

		vecB = vld1q(pSrcB);
		pSrcB += 4;

		vecSum = vfmaq(vecSum, vecA, vecB);
		/*
		 * Decrement the blockSize loop counter
		 */
		blkCnt --;
	}


	blkCnt = blockSize & 3;
	if (blkCnt > 0U) {
		/* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */

		mve_pred16_t p0 = vctp32q(blkCnt);
		vecA = vld1q(pSrcA);
		vecB = vld1q(pSrcB);
		vecSum = vfmaq_m(vecSum, vecA, vecB, p0);
	}

	sum = vecAddAcrossF32Mve(vecSum);

	/* Store result in destination buffer */
	*result = sum;

}

#else

void arm_dot_prod_f32(
	const float32_t *pSrcA,
	const float32_t *pSrcB,
	uint32_t blockSize,
	float32_t *result)
{
	uint32_t blkCnt;                               /* Loop counter */
	float32_t sum = 0.0f;                          /* Temporary return variable */

#if defined(ARM_MATH_NEON) && !defined(ARM_MATH_AUTOVECTORIZE)
	f32x4_t vec1;
	f32x4_t vec2;
	f32x4_t accum = vdupq_n_f32(0);
	f32x2_t tmp = vdup_n_f32(0);

	/* Compute 4 outputs at a time */
	blkCnt = blockSize >> 2U;

	vec1 = vld1q_f32(pSrcA);
	vec2 = vld1q_f32(pSrcB);

	while (blkCnt > 0U) {
		/* C = A[0]*B[0] + A[1]*B[1] + A[2]*B[2] + ... + A[blockSize-1]*B[blockSize-1] */
		/* Calculate dot product and then store the result in a temporary buffer. */

		accum = vmlaq_f32(accum, vec1, vec2);

		/* Increment pointers */
		pSrcA += 4;
		pSrcB += 4;

		vec1 = vld1q_f32(pSrcA);
		vec2 = vld1q_f32(pSrcB);

		/* Decrement the loop counter */
		blkCnt--;
	}

#if __aarch64__
	sum = vpadds_f32(vpadd_f32(vget_low_f32(accum), vget_high_f32(accum)));
#else
	tmp = vpadd_f32(vget_low_f32(accum), vget_high_f32(accum));
	sum = vget_lane_f32(tmp, 0) + vget_lane_f32(tmp, 1);

#endif

	/* Tail */
	blkCnt = blockSize & 0x3;

#else
#if defined (ARM_MATH_LOOPUNROLL) && !defined(ARM_MATH_AUTOVECTORIZE)

	/* Loop unrolling: Compute 4 outputs at a time */
	blkCnt = blockSize >> 2U;

	/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
	 ** a second loop below computes the remaining 1 to 3 samples. */
	while (blkCnt > 0U) {
		/* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */

		/* Calculate dot product and store result in a temporary buffer. */
		sum += (*pSrcA++) * (*pSrcB++);

		sum += (*pSrcA++) * (*pSrcB++);

		sum += (*pSrcA++) * (*pSrcB++);

		sum += (*pSrcA++) * (*pSrcB++);

		/* Decrement loop counter */
		blkCnt--;
	}

	/* Loop unrolling: Compute remaining outputs */
	blkCnt = blockSize % 0x4U;

#else

	/* Initialize blkCnt with number of samples */
	blkCnt = blockSize;

#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
#endif /* #if defined(ARM_MATH_NEON) */

	while (blkCnt > 0U) {
		/* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */

		/* Calculate dot product and store result in a temporary buffer. */
		sum += (*pSrcA++) * (*pSrcB++);

		/* Decrement loop counter */
		blkCnt--;
	}

	/* Store result in destination buffer */
	*result = sum;
}

#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
/**
  @} end of BasicDotProd group
 */
